Data Science in Marketing: An Introduction Course 2022

Description

Welcome to the Data Science in Marketing: An Introduction Course 2021

This course teaches you how Data Science can be used to solve real-world business problems and how you can apply these techniques to solve real-world case studies.

Traditional Businesses are hiring Data Scientists in droves, and knowledge of how to apply these techniques in solving their problems will prove to be one of the most valuable skills in the next decade!

"Data Scientist has become the top job in the US for the last 4 years running!" according to Harvard Business Review & Glassdoor.

However, Data Science has a difficult learning curve - How does one even get started in this industry awash with mystique, confusion, impossible-looking mathematics, and code? Even if you get your feet wet, applying your newfound Data Science knowledge to a real-world problem is even more confusing.

This course seeks to fill all those gaps in knowledge that scare off beginners and simultaneously apply your knowledge of Data Science to real-world business problems.

This course has a comprehensive syllabus that tackles all the major components of Data Science knowledge.

Our Learning path includes:

1. How Data Science and Solve Many Common Marketing Problems

2. The Modern Tools of a Data Scientist - Python, Pandas, Scikit-learn, and Matplotlib.

3. Machine Learning Theory - Linear Regressions,  Decision Trees, and Model Assessment.

4. Data Science in Marketing - Modelling Engagement Rates.

5. Data Science in Retail - Customer Segmentation, Lifetime Value, and Customer/Product Analytics

6. Unsupervised Learning - K-Means Clustering.

7. Recommendation Systems - Collaborative Filtering.

Four (3) Data Science in Marketing Case Studies:

1. Analysing Conversion Rates of Marketing Campaigns.

2. Predicting Engagement - What drives ad performance?

3. Who are Your Best Customers? & Customer Lifetime Values (CLV).

Four (2) Retail Data Science Case Studies:

1. Product Analytics (Exploratory Data Analysis Techniques

2. Product Recommendation Systems.

Businesses NEED Data Scientists more than ever. Those who ignore this trend will be left behind by their competition. In fact, the majority of new Data Science jobs won't be created by traditional tech companies (Google, Facebook, Microsoft, Amazon, etc.) they're being created by your traditional non-tech businesses. The big retailers, banks, marketing companies, government institutions, insurances, real estate and more.

"Consumer data will be the biggest differentiator in the next two to three years. Whoever unlocks the reams of data and uses it strategically will win.”

With Data Scientist salaries creeping up higher and higher, this course seeks to take you from a beginner and turn you into a Data Scientist capable of solving challenging real-world problems.

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Data Scientist is the buzz of the 21st century for good reason! The tech revolution is just starting and Data Science is at the forefront. Get a head start applying these techniques to all types of Marketing problems by taking this course!

What You Will Learn!

• Pandas
• JSON
• Handling missing data
• Decision Tree
• Collaborative filtering
• Data Cleanup
• Linear Regression Model
• Evaluating model Performance
• K-means
• Analyzing Customer lifetime value
• Product analytics
• Product Recommendation system
• Interpreting customer segments
• Analyzing and visualizing KPI

Who Should Attend!

• Beginners to Data Science
• Business Analysts who wish to do more with their data
• College graduates who lack real world experience
• Business oriented persons (Management or MBAs) who'd like to use data to enhance their business
• Software Developers or Engineers who'd like to start learning Data Science
• Anyone looking to become more employable as a Data Scientist
• Anyone with an interest in using Data to Solve Real World Problems

TAKE THIS COURSE